1∶2000成图比例尺数字航空摄影测量质量控制与保障

通过《太原市1∶2 000成图比例尺数字航空摄影测量》项目实践,以该项目中1∶2 000数字线划图制作为例,结合数据分层详细介绍了数字摄影测量中的质量控制与保障的措施,以供类似测量工作借鉴。     

Autonomous Variable‐Resolution Map Building for Mobile Robots in Unknown Environments

This paper presents a method that allows simultaneous map building and path planning for mobile robots in unknown environments. A graphical representation of a workspace in variable resolutions is constructed using measurement data obtained by omnidirectional distance sensors. At the same time, a search for a feasible path to the target destination is executed using the constructed graph map. The proposed method is evaluated by performing simulations and experiments using an omnidirectional mobile robot equipped with laser range finders. © 2013 Wiley Periodicals, Inc. Electr Eng Jpn, 186(4): 59–69, 2014; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.22493     

Weighted archetypal analysis of the multi-element graph for query-focused multi-document summarization

Most existing research on applying the matrix factorization approaches to query-focused multi-document summarization (Q-MDS) explores either soft/hard clustering or low rank approximation methods. We employ a different kind of matrix factorization method, namely weighted archetypal analysis (wAA) to Q-MDS. In query-focused summarization, given a graph representation of a set of sentences weighted by similarity to the given query, positively and/or negatively salient sentences are values on the weighted data set boundary. We choose to use wAA to compute these extreme values, archetypes, and hence to estimate the importance of sentences in target documents set. We investigate the impact of using the multi-element graph model for query focused summarization via wAA. We conducted experiments on the data of document understanding conference (DUC) 2005 and 2006. Experimental results evidence the improvement of the proposed approach over other closely related methods and many of state-of-the-art systems.     

Guided curation of semistructured data in collaboratively-built knowledge bases

The collaborative curation of semistructured knowledge has become a popular paradigm on the web and also within enterprises. In such knowledge bases a common structure of the stored information is crucial for providing efficient and precise search facilities. However, the task of refining, extending and homogenizing knowledge and its structure is very complex. In this article we present two paradigms for the simplification of this task by providing guidance mechanisms to the user. Both paradigms aim at combining the power of automated extraction algorithms with the semantic awareness of human users to accomplish this refinement task.     

The impact of study load on the dynamics of longitudinal email communications among students

With the advent of information technology, emails have gained wide acceptability among students as an asynchronous communication tool. According to the current pedagogy literature the overall trend of the use of email communication by university students has been increasing significantly since its inception, despite the rapid growth of the popularity and acceptability of other social mediums (e.g. Mobile phone and Facebook). In this study, we explore a longitudinal email communication network, which evolved under an increasing study load among 38 students throughout a university semester, using measures of social network analysis (SNA) and exponential random graph (ERG) models. This longitudinal network was divided into three waves, where each wave represents the portion of the complete longitudinal network that evolves between two consecutive observations. An increased study load was imposed through the assessment components of the course. SNA measures of degree centrality (i.e. the activity of an actor or actor popularity), betweenness centrality (i.e. the capacity to control the flow of information in a network), closeness centrality (i.e. reachable to other nodes) and reciprocity (i.e. tendency to make reciprocal links) are considered to explore this longitudinal network. ERG models are probabilistic models that are presented by locally determined explanatory variables and can effectively identify structural properties of networks. From the analysis of this email communication network, we notice that students' network positions and behaviours change with the changes in their study load. In particular, we find that (i) students make an increased number of email communications with the increase of study load; (ii) the email communication network become sparse with the increase of study load; and (iii) the 2-star parameter (a subset of three nodes in which one node is connected to each of the other two nodes) and the triangle parameter (a subset of three nodes in which each node is connected to the other two nodes) can effectively explain the formation of network in wave3; whereas, the 3-star parameter (a subset of four nodes in which one node is connected to each of other three nodes) can effectively explain the formation of network in wave1 and wave2. Interpretations of these findings for the monitoring of student behaviour in online learning environments, as well as the implications for the design of assessment and the use of asynchronous tools are discussed in this paper.     

基于网络拓扑特性的MCI分类

阿尔茨海默氏病(Alzheimer's disease,AD)和轻度认知障碍(Mild cognitive impairment,MCI)是经常发生在老年人中的脑疾病,其主要表现为认知和智力的障碍.机器学习和模式识别方法已经被应用到对AD和MCI的诊断和分类中.最近,研究人员提出利用大脑连接网络实现对疾病的诊断和分类.大部分的研究主要集中在网络中提取一些局部的特性(如聚类系数),并利用机器学习的方法(如支持向量机)来实现对疾病的分类.然而,存在的研究表明AD以及MCI是和一个大规模的脑连接网络相关,而不仅是大脑的若干区域.因此,本文提出一种新的基于网络整体拓扑结构信息的分类方法,并将其用于对MCI疾病的分类.实验结果表明,本文的方法能够对分类结果有重要的改进.     

基于二分图的宝鸡公交线路-站点网络建模及分析

复杂网络理论已成为研究交通系统的有效工具。以陕西省宝鸡市的43个公交线路及344个公交站点数据为基础,基于二分图理论,构建了站点-线路公交网络模型,并对该网络的统计性质进行了分析。研究结果表明,网络中的线路节点度分布呈现泊松分布,大部分线路度值集中在平均值附近;而站点节点度分布呈现幂律分布,其中的少数节点高度连接,为网络中的关键枢纽节点。这些高度连接的线路和站点可被筛选为宝鸡市交通网络研究中的重点规划对象。     

Efficient constraint reduction in multistage stochastic programming problems with endogenous uncertainty

Multistage stochastic programming with endogenous uncertainty is a new topic in which the timing of uncertainty realization is decision-dependent. In this case, the number of nonanticipativity constraints (NACs) increases very quickly with the number of scenarios, making the problem computationally intractable. Fortunately, a large number of NACs are typically redundant and their elimination leads to a considerable reduction in the problem size. Identifying redundant NACs has been addressed in the literature only in the special case where the scenario set is equal to the Cartesian product of all possible outcomes for endogenous parameters; however, this is a scarce condition in practice. In this paper, we consider the general case where the scenario set is an arbitrary set; and two approaches, able to identify all redundant NACs, are proposed. The first approach is by mixed integer programming formulation and the second one is an exact polynomial time algorithm. Proving the fact that the proposed algorithm is able to make the uppermost reduction in the number of NACs is another novelty of this paper. Computational results evaluate the efficiency of the proposed approaches.     

Enabling machine understandable exchange of energy consumption information in intelligent domotic environments

In the 21st century, all the major countries around the world are coming together to reduce the impact of energy generation and consumption on the global environment. Energy conservation and its efficient usage has become a top agenda on the desks of many governments. In the last decade, the drive to make homes automated and to deliver a better assisted living picked pace and the research into home automation systems accelerated, usually based on a centralized residential gateway. However most devised solutions fail to provide users with information about power consumption of different house appliances. The ability to collect power consumption information can lead us to have a more energy efficient society. The goal addressed in this paper is to enable residential gateways to provide the energy consumption information, in a machine understandable format, to support third party applications and services. To reach this goal, we propose a Semantic Energy Information Publishing Framework. The proposed framework publishes, for different appliances in the house, their power consumption information and other properties, in a machine understandable format. Appliance properties are exposed according to the existing semantic modeling supported by residential gateways, while instantaneous power consumption is modeled through a new modular Energy Profile ontology.     

用于固体火箭发动机药浆浇注的阀控式液压激振系统的建模

论述了阀控式液压振动技术在某型号固体火箭发动机药浆浇注系统中的应用,对这种新型的旋转阀控式液压激振系统的控制原理进行了分析,并运用键合图理论进行了液压系统建模,推导出系统状态方程,绘制了Simulink模型。